%0 Journal Article %1 newman2005measure %A Newman, M.E. J. %D 2005 %J Social Networks %K betweenness-centrality networks random-walks %N 1 %P 39 - 54 %R https://doi.org/10.1016/j.socnet.2004.11.009 %T A measure of betweenness centrality based on random walks %U http://www.sciencedirect.com/science/article/pii/S0378873304000681 %V 27 %X Betweenness is a measure of the centrality of a node in a network, and is normally calculated as the fraction of shortest paths between node pairs that pass through the node of interest. Betweenness is, in some sense, a measure of the influence a node has over the spread of information through the network. By counting only shortest paths, however, the conventional definition implicitly assumes that information spreads only along those shortest paths. Here, we propose a betweenness measure that relaxes this assumption, including contributions from essentially all paths between nodes, not just the shortest, although it still gives more weight to short paths. The measure is based on random walks, counting how often a node is traversed by a random walk between two other nodes. We show how our measure can be calculated using matrix methods, and give some examples of its application to particular networks.

@article{newman2005measure, abstract = {Betweenness is a measure of the centrality of a node in a network, and is normally calculated as the fraction of shortest paths between node pairs that pass through the node of interest. Betweenness is, in some sense, a measure of the influence a node has over the spread of information through the network. By counting only shortest paths, however, the conventional definition implicitly assumes that information spreads only along those shortest paths. Here, we propose a betweenness measure that relaxes this assumption, including contributions from essentially all paths between nodes, not just the shortest, although it still gives more weight to short paths. The measure is based on random walks, counting how often a node is traversed by a random walk between two other nodes. We show how our measure can be calculated using matrix methods, and give some examples of its application to particular networks.}, added-at = {2018-12-20T07:28:36.000+0100}, author = {Newman, M.E. J.}, biburl = {https://www.bibsonomy.org/bibtex/2d751ebdedbaaf2c5530a649a11de5dad/karthikraman}, description = {A measure of betweenness centrality based on random walks - ScienceDirect}, doi = {https://doi.org/10.1016/j.socnet.2004.11.009}, interhash = {acf65bd79746305644f779aff46ea18d}, intrahash = {d751ebdedbaaf2c5530a649a11de5dad}, issn = {0378-8733}, journal = {Social Networks}, keywords = {betweenness-centrality networks random-walks}, number = 1, pages = {39 - 54}, timestamp = {2018-12-20T07:28:36.000+0100}, title = {A measure of betweenness centrality based on random walks}, url = {http://www.sciencedirect.com/science/article/pii/S0378873304000681}, volume = 27, year = 2005 }